Design and Implementation of a Fuzzy Inference Model for Mapping the Sustainability of Energy Crops

Design and Implementation of a Fuzzy Inference Model for Mapping the Sustainability of Energy Crops

Fausto Cavallaro (University of Molise Via De Sanctis, Italy) and Luigi Ciraolo (University of Messina, Italy)
DOI: 10.4018/978-1-4666-6631-3.ch003


Energy crops are positioned as the most promising renewable energy sources. Over recent years, the use of biomass has been growing significantly, especially in countries that have made a strong commitment to renewable sources in their energy policies. One of the aspects of the use of biomass for energy is that it is still controversial with regard to full environmental sustainability. Unfortunately, the existing environmental evaluation tools in many cases are unable to manage uncertain input data. Fuzzy-set-based methods, instead, have proved to be able to deal with uncertainty in environmental topics. The idea of this chapter is to reproduce a solution by decoding it from the domain of knowledge with the calculus of fuzzy “if-then” rules. A methodology based on Fuzzy Inference Systems (FIS) is proposed to assess the environmental sustainability of biomass.
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2. Fuzzy Sets And Uncertainty

The use of fuzzy set theory has yielded very good results for modelling qualitative information. Fuzziness measures to what extent something is found or to what degree a condition holds. The introduction of fuzzy logic therefore modifies considerably all the underlying principles of traditional logic. Fuzzy systems are an alternative to traditional notions of logic that have their origins in ancient Greek philosophy.

Zadeh highlights the gap existing between mental representations of reality and traditional mathematical representations. Classical logic based on exact numbers is too rigid to account for classes of objects of the physical world in which membership appears as a gradual notion (Dubois, Ostasiewicz, & Prade, 2000).

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